• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.107-115
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• 2016

In this paper, we propose a Bicycle sharing has grown popular around the cities in the world due to its convenience. However, the bicycle sharing system is not problem-free, and there remains many managerial problems to be solved. In this study, we analyzed pricing strategy of a bicycle sharing system by minimizing the number of bicycles relocated by trucks, the act of which incurs penalty. The objective function is constructed by applying mixed integer programming and is presented as a stochastic model by using Markov chain so that arrival and departure rates of bicycle stations can be utilized in the analysis. The efficiency of the presented model is verified upon the analysis of bicycle sharing data gathered in Daejeon in 2014.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.33 no.12
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• pp.53-62
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• 2017

Many gradient-based mathematical methods have been developed and are in use for structural size optimization problems, in which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. The main objective of this paper is to propose an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm that is derived using penalty function. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. In this paper, a discrete search strategy using the HS algorithm with a static penalty function is presented in detail and its applicability using several standard truss examples is discussed. The numerical results reveal that the HS algorithm with the static penalty function proposed in this study is a powerful search and design optimization technique for structures with discrete-sized members.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.5
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• pp.785-790
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• 2008

A technique for determining the feedback gain of the states feedback controller using a real-coded genetic algorithm(RCGA) is presented. It is concerned with the states error to the performance index of a RCGA. As for assessing the performance of the controller three performance criteria (ISE. IAE and ITAE) are adopted. And designing the controller involves a constrained optimization problem. Therefore a real-coded genetic algorithm incorporating the penalty strategy is used. The performance of the proposed method is demonstrated through a set of simulation about an inverted pendulum system.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.268-275
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• 2000

The increasing technological demands of today call for complex systems, which in turn involve a series of optimization problems with some equality or inequality constraints. In this paper, we presents a real-coded genetic algorithm(RCGA) as an optimization tool which is implemented by three genetic operators based on real coding representation. Through a lot of simulation works, the optimum settings of its control parameters are obtained on the basis of global off-line robustness for use in off-line applications. Two optimization problems are Presented to illustrate the usefulness of the RCGA. In case of a constrained problem, a penalty strategy is incorporated to transform the constrained problem into an unconstrained problem by penalizing infeasible solutions.

• Steel and Composite Structures
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• v.33 no.2
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• pp.163-180
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• 2019

A semi analytical method is employed to analyze free vibration characteristics of uniform and stepped functionally graded circular cylindrical shells under complex boundary conditions. The analytical model is established based on multi-segment partitioning strategy and first-order shear deformation theory. The displacement functions are handled by unified Jacobi polynomials and Fourier series. In order to obtain continuous conditions and satisfy complex boundary conditions, the penalty method about spring technique is adopted. The solutions about free vibration behavior of functionally graded circular cylindrical shells were obtained by approach of Rayleigh-Ritz. To confirm the dependability and validity of present approach, numerical verifications and convergence studies are conducted on functionally graded cylindrical shells under various influencing factors such as boundaries, spring parameters et al. The present method apparently has rapid convergence ability and excellent stability, and the results of the paper are closely agreed with those obtained by FEM and published literatures.

• Journal of Korean Association for Spatial Structures
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• v.4 no.4 s.14
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• pp.91-98
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• 2004

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. This method is an unconstrained optimization technique, so the constraints are handled in an implicit manner. The most popular way of handling constraints is to transform the original constrained problem into an unconstrained problem, using the concept of penalty function. I present the 3 fitness functions which represent the reject strategy, the penalty strategy, and the combined strategy. I make the design program using the 3 fitness Auctions and it is applied to the design problem of a gable frame and a 2 story 3 span frame.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.816-818
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• 2005

In this paper, we have developed an hourly operating strategy for Direct load control (DLC) considering the efficiency of DLC program and increasing the utility of DLC resource. According to the operating code for DLC, the DLC center should curtail the load for 4 hours when the control notification has been enforced. Since the above strategy may limit the participation of entities, who intend to take part in the DLC program, the new strategy to mitigate the above limitation is required. In this paper, we have developed the operating strategy of DLC program and the mechanism to apply the proposed strategy in the DLC center. The proposed strategy makes the important role from the view of guaranteing the effective alternative raising the participation and avoiding the penalty of the entities.

• Korean Journal of Cognitive Science
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• v.28 no.1
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• pp.65-90
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• 2017

Rewards or penalties become informative only when contingent on an immediately preceding response. Our goal was to determine if the brain responds differently to motivational events depending on whether they provide feedback with the contingencies effective for learning. Event-related fMRI data were obtained from 22 volunteers performing a visuomotor categorical task. In learning-condition trials, participants learned by trial and error to make left or right responses to letter cues (16 consonants). Monetary rewards (+500) or penalties (-500) were given as feedback (learning feedback). In random-condition trials, cues (4 vowels) appeared right or left of the display center, and participants were instructed to respond with the appropriate hand. However, rewards or penalties (random feedback) were given randomly (50/50%) regardless of the correctness of response. Feedback-associated BOLD responses were analyzed with ANOVA [trial type (learning vs. random) x feedback type (reward vs. penalty)] using SPM8 (voxel-wise FWE p < .001). The right caudate nucleus and right cerebellum showed activation, whereas the left parahippocampus and other regions as the default mode network showed deactivation, both greater for learning trials than random trials. Activations associated with reward feedback did not differ between the two trial types for any brain region. For penalty, both learning-penalty and random-penalty enhanced activity in the left insular cortex, but not the right. The left insula, however, as well as the left dorsolateral prefrontal cortex and dorsomedial prefrontal cortex/dorsal anterior cingulate cortex, showed much greater responses for learning-penalty than for random-penalty. These findings suggest that learning-penalty plays a critical role in learning, unlike rewards or random-penalty, probably not only due to its evoking of aversive emotional responses, but also because of error-detection processing, either of which might lead to changes in planning or strategy.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.699-704
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• 2000

The present paper deals with a multiobjective optimization method based on the co-evolutionary genetic strategy. The co-evolutionary strategy carries out the multiobjective optimization in such way that it optimizes individual objective function as compared with each generation's value while there are more than two genetic evolutions at the same time. In this study, the designs that are out of the given constraint map compared with other objective function value are excepted by the penalty. The proposed multiobjective genetic algorithms are distinguished from other optimization methods because it seeks for the optimized value through the simultaneous search without the help of the single-objective values which have to be obtained in advance of the multiobjective designs. The proposed strategy easily applied to well-developed genetic algorithms since it doesn't need any further formulation for the multiobjective optimization. The paper describes the co-evolutionary strategy and compares design results on the simple structural optimization problem.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.1-19
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• 1999

It is truism to say that today's customers demand high quality products and services; nevertheless, nowhere is this more prevalent than in the medical industry. Korea's globalization has increased it's citizen's awareness of greater life expectancies and medical improvements in other regions of the globe. Therefore, it is universally essential that in order to be successful in the medical industry, vendors must meet the ever increasing demands of better educated customers. The purpose of this study was twofold: 1) The first objective was discover what health care services are in demand and the quality factors related to these services. 2) The second objective was to determine a strategy for improving health care service through quality function deployment(QFD). One hundred and ninety-five respondents were randomly selected and asked to fill out a questionnaire after having undergone treatment at a medical clinic, located in Daejon, South Korea. The questionnaire was designed to obtain information about both he clients' satisfaction with, and their sense of the value of the medical treatment they received. Penalty-reward analysis and QFD were used to interpret the survey results and to deploy the collective voices of the customers. The results of the penalty-reward analysis illustrated that the 'communication' service quality factor was classified into an excitement factor that incurs no penalty if not achieved but adds value if the requirement is exceeded. As a result of the QFD analysis on the 'communication' service quality factor, eleven strategic alternatives were prioritized, and isolated a vital service quality characteristic. This characteristic can be implemented to bring value-added changes for the improvement of health care services.